期刊
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
卷 20, 期 4, 页码 507-517出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/073500102288618649
关键词
bootstrapping; empirical likelihood; panel data
Generalized method of moments (GMM) has been an important innovation in econometrics. Its usefulness has motivated a search for good inference procedures based on GMM. This article presents a novel method of bootstrapping for GMM based on resampling from the empirical likelihood distribution that imposes the moment restrictions. We show that this approach yields a large-sample improvement and is efficient, and give examples. We also discuss the development of GMM and other recent work on improved inference.
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